Summer community structure of aerobic anoxygenic phototrophic bacteria in the western Arctic ...

48 Pages·2017·3.17 MB·English

Page 1 of 47 FEMS Microbiology Ecology
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3 FEMSEC-12-12-0621.R1
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8 Summer community structure of aerobic anoxygenic phototrophic bacteria in
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the western Arctic Ocean
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Dominique Boeuf1,2, Matthew T. Cottrell3, David L. Kirchman3, Philippe Lebaron4,5 & Christian
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20 Jeanthon1,2
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1UPMC, Univ Paris VI, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique,
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27 Roscoff, France e
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29 2CNRS, UMR 7144, Adaptation et Diversité en Milieu Marin, Station Biologique, Roscoff, France
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31 3School of Marine Science and Policy, University of Delaware, Lewes, Delaware, USA
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33 4UPMC, Univ Paris VI, UMR 7621, LOMIC, ObservaRtoire Océanologique, Banyuls-sur-mer, France
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5CNRS, UMR 7621, LOMIC, Observatoire Océanologique, Banyuls-sur-mer, France
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40 Correspondence: Christian Jeanthon, Station Biologique, Place Georges Teissier, 29680
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Roscoff, France. Phone : [phone] ; Fax : [phone] ; E-mail: jeanthon@sb-
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45 roscoff.fr
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Running title: AAP bacteria in the western Arctic Ocean
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52 Keywords: photoheterotroph; aerobic anoxygenic phototrophic bacteria; pufM gene;
53 bacteriochlorophyll; Arctic Ocean; Mackenzie River
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FEMS Microbiology Ecology Page 2 of 47
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3 Abstract
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Aerobic anoxygenic phototrophic (AAP) bacteria are found in a range of aquatic and
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8 terrestrial environments, potentially playing unique roles in biogeochemical cycles. Although
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known to occur in the Arctic Ocean, their ecology and the factors that govern their
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13 5 community structure and distribution in this extreme environment are poorly understood.
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15 Here, we examined summer AAP abundance and diversity in the North East Pacific and the
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Arctic Ocean with emphasis on the southern Beaufort Sea. AAP bacteria comprised up to 10
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20 and 14% of the prokaryotic community in the bottom nepheloid layer and surface waters of
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22 the Mackenzie plume, resrpectively. However, relative AAP abundances were low in offshore
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10 waters. Environmental pufM clone libraries revealed that AAP bacteria in the
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27 Alphaproteobacteria and Betaproeteobacteria classes dominated in offshore and in river-
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29 influenced surface waters, respectively. The most frequent AAP group was a new
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uncultivated betaproteobacterial clade whose abundance decreased along the salinity
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34 gradient of the Mackenzie plume even though their photosynthetic genes were actively
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15 expressed in offshore waters. Our data indicate that AvAP bacterial assemblages represented
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a mixture of freshwater and marine taxa mostly restricted to the Arctic Ocean and highlight
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41 the substantial influence of riverine inputs on their distribution in coastal environments.
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Page 3 of 47 FEMS Microbiology Ecology
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3 25 Introduction
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Aerobic anoxygenic phototrophic (AAP) bacteria are photoheterotrophs that require
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8 oxygen for their growth and for bacteriochlorophyll a (Bchl a) synthesis. They inhabit a wide
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variety of illuminated habitats in diverse terrestrial, freshwater, and marine environments
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(Béjà et al., 2002; Csotonyi et al., 2010; Atamna-Ismaeel et al., 2012). First discovered in
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15 30 coastal marine waters (Shiba et al., 1979), AAP bacteria have been intensively studied in the
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marine environment (Cottrell et al., 2006; Mašín et al., 2006; Lehours et al., 2010). Their
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20 abundance and distribution vary greatly among oceanic regimes, suggesting that there is a
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22 broad range of potential recological niches for these microbes. AAP bacteria seem to be more
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abundant in shelf and coastal areas than in the open ocean (Schwalbach & Fuhrman, 2005;
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27 35 Sieracki et al., 2006). Although theeir abundance can be high in some oligotrophic regions
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29 (Lami et al., 2007), AAP bacteria typically constitute a small percentage (2 to 4%) of total
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prokaryotes in oceanic environments (Cottrell et al., 2006; Jiao et al., 2007). However, their
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34 proportions can exceed 10% in eutrophic estuaries (Waidner & Kirchman, 2007). Despite the
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lower abundances in most oligotrophic pelagic marine environments, AAP bacteria
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39 40 constitute a very dynamic part of the bacterial community and potentially contribute
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41 significantly to the cycling of organic carbon in the upper ocean (Koblížek et al., 2007).
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Culture-dependent and -independent studies have shown AAP bacteria to be genetically
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46 diverse with members of the Alpha-, Beta-, and Gammaproteobacteria (Béjà et al., 2002;
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48 Yutin et al., 2007; Jeanthon et al., 2011). The environmental factors controlling the
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45 population structure and diversity of these photoheterotrophic bacteria remain poorly
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53 understood.
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55 Arctic marine ecosystems are characterized by strong seasonality in incident light, ice
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cover, temperature, and river discharge which affect salinity and other biogeochemical
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FEMS Microbiology Ecology Page 4 of 47
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3 properties. In the Beaufort Sea, the Mackenzie River delivers considerable freshwater,
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5 50 nutrients and organic matter which exert strong controls on the productivity, salinity and
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water circulation (Aagaard & Carmack, 1989; Opsahl et al., 1999). Despite a short growing
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10 season and extensive sea ice coverage, the most river-influenced of the world's oceans
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supports a productive aquatic ecosystem. Recent studies over the Mackenzie Shelf in the
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Beaufort Sea have revealed diverse and active communities of Bacteria and Archaea that
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Our current knowledge of the abundance, distribution, and activity of AAP bacteria in
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22 perennially cold marine wraters is still limited. In the only study in the Arctic, AAP bacteria
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24 contributed 5 to 8% of the total prokaryotic community in spatially close coastal sites of the
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western Beaufort and eastern Chukchi Seas (Cottrell & Kirchman, 2009). Seasonal shifts in
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31 abundance of the total prokaryotic community. There were no substantial shifts in the
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community structure of AAP bacteria between the two seasons. Although pufM genes in
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36 Arctic surface waters could be assigned to taxonomic groups previously identified in
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metagenomic shotgun sequences from the GOS expedition (Yutin et al., 2007), their
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65 sequences were distinct from those retrieved in lower-latitude waters (Cottrell & Kirchman,
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43 2009).
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In this study, we collected samples across a several-thousand kilometers transect
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above the 60°N latitude that yielded an unprecedented resolution of the Beaufort Sea during
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50 summer and explored transition zones between offshore and large Arctic rivers that have a
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70 major influence on coastal ocean biogeochemistry. To examine the AAP bacterial community
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55 structure and factors that govern it, we combined the use of infrared epifluorescence
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57 microscopy and culture-dependent and independent approaches. The Beaufort Shelf surface
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Page 5 of 47 FEMS Microbiology Ecology
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3 circulation is strongly influenced by ice, winds and freshwater input resulting from river
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5 discharge and sea-ice melt. We hypothesized that AAP bacterial abundance and composition
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75 would change substantially along this transect and that riverine inputs would have a
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10 substantial influence on the AAP bacterial populations.
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Materials and methods
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20 80 Study area, sampling and oceanographic parameters
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22 The MALINA cruise took rplace onboard the Canadian research icebreaker CCGS Amundsen
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during summer 2009 from Victoria (BC, Canada) to the Beaufort Sea (Leg 1b) and then
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27 throughout the Beaufort Sea (Leg e2b) (Fig.1). Most of the stations sampled on the west–east
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29 transect in the Beaufort Sea (leg2) were ice-free. However, surface waters of eastward
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85 offshore waters were still ice-covered. Surface seawater samples were collected with an acid
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34 cleaned bucket during Leg 1b and in the Mackenzie plume (stations 395, 398, 694, and 697)
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during Leg 2b. In the Beaufort Sea, seawater was collected from six depths using Niskin
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bottles mounted on a CTD (conductivity temperature depth probe) rosette. Ancillary data of
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41 temperature, salinity, pH, dissolved oxygen, colored dissolved organic matter, inorganic and
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90 organic nutrients, and chlorophyll a are given in Table S1.
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46 Bacterioplankton biomass for DNA and total RNA extraction were collected onboard.
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48 Seawater samples were prefiltered through 47 mm diameter and 3 µm pore size
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polycarbonate filters (Cyclopore, Whatman, USA) before the final collection of
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53 bacterioplankton cells onto 0.22 μm-pore-size Sterivex cartridges (Millipore, USA) for DNA
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55 95 extraction or onto 27 mm diameter and 0.22 µm-pore-size Durapore filters (Millipore, USA)
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for RNA extraction. Sterivex cartridges were filled with 1.6 ml of lysis buffer (0.75 M sucrose,
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FEMS Microbiology Ecology Page 6 of 47
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3 50 mM Tris-HCl, pH 8), immediately frozen in liquid nitrogen, and stored at -80°C until
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5 analysis. To limit the degradation of mRNA, small volumes of seawater (~ 1 liter) were
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filtered as rapidly as possible, immediately upon retrieval of the CTD. RNA filters were
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10 100 transferred in collection tubes containing 0.8 ml of RLT buffer (Qiagen, Hamburg, Germany)
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with 1 % of β-mercaptoethanol, frozen in liquid nitrogen, and stored at -80°C until analysis.
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The time from the start of filtration to storage was 15-20 min.
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Microscopic enumeration of AAP bacteria and total prokaryotes
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22 105 Prokaryotes were enumrerated by epifluorescence microscopy of paraformaldehyde-fixed
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2006). Filters were stored at -80°C for up to 4 months prior to analysis. Total prokaryotes
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29 were enumerated after staining withe 4’,6-diamidino-2-phenylindole (DAPI), 1 μg.ml−1 final
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31 concentration in 1× phosphate-buffered saline (PBS) for 10 min. The AAP bacteria were
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110 enumerated using an Intensified Retiga charge-couple device camera (Qimaging, Surry, BC
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36 Canada) and image analysis routines to enumerate cells that fluoresce blue when stained
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with DAPI and have infrared fluorescence (BChl a signal), but not red or orange fluorescence
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(Chl a and phycoerythrin signals, respectively) (Cottrell et al., 2006). AAP bacterial
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43 abundance data were imported into Ocean Data View version 4 (Schlitzer, 2010) and
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115 interpolated using the DIVA gridding tool.
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Isolation and identification of AAP bacterial strains
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55 Seawater samples (50-100 µl) collected at the surface and at the deep chlorophyll maximum
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Page 7 of 47 FEMS Microbiology Ecology
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3 prepared using seawater collected at station 860 at the surface and the DCM, respectively.
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5 Dimethylsulfoniopropionate (DMSP) was added to the medium at a final concentration of
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100 nM. Culture plates were incubated for up to 2 months at 4°C into thermostatic cabinets
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10 illumined by luminescent tubes at irradiance levels of 120 µmol photons m-2 s-1 (for surface
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detected as previously described (Jeanthon et al., 2011).
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17 Bacterial DNA was extracted using the QuickExtract™ Bacterial DNA Extraction Kit
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(Epicentre Biotechnologies, Madison, WI, USA). Small-subunit (16S) rRNA genes were
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22 amplified by polymeraser chain reaction (PCR) using universal reverse primer 1492R and
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hexachlorofluorescein (6-HEX) and with 6-carboxyfluorescein (6-FAM), respectively. Reaction
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29 mixtures (25 μL) contained 5 X buffer (5 μl), 2mM MgCl2, 10 pmoles of each
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31 deoxyribonucleotide triphosphate (dATP, dCTP, dGTP, dTTP; Eurogentec, Seraing, Belgium),
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10 pmoles of each oligonucleotide primer, 1.25 U of GoTaq Flexi DNA polymerase (Promega,
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the reaction mixture at 95 °C for 5 min, and the thermal profile then consisted of 30 cycles of
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denaturation at 95 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 1.5 min.
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43 A final extension step was carried out at 72 °C for 10 min. The PCR products were digested
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with the restriction endonucleases HinfI and MspI (New England BioLabs, Ipswich, MA, USA)
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fragments (T-RFs) were separated in a 3130 xl Genetic Analyzer (Applied Biosystems). Data
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55 were analyzed using the PeakScanner™ Software (Applied Biosystems).
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FEMS Microbiology Ecology Page 8 of 47
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3 16S rRNA gene sequences of at least two randomly chosen strains from each T-RFLP
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conditions as described above. PCR products were purified by ExoSAP-IT PCR purification kit
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10 (GE Healthcare) and sequenced using the latter primers with an ABI 3130 POP7 sequencer
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(Applied Biosystems).
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16S rRNA gene sequences were compared to sequences in public databases with
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17 150 BLASTn (Altschul et al 1997). The new sequences were aligned using the Q-INS-I algorithm of
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the MAFFT sequence alignment program version 6.5 (Katoh et al 2009). A set of 16S rRNA
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22 sequences with high simirlarity to those determined in this study were retrieved and added
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parsimony and maximum likelihood inference approaches using MEGA 5 (Tamura et al
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29 155 2011). Bayesian analyses (MrBayes; (Ronquist and Huelsenbeck 2003) were also performed
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31 to provide additional statistical support for the nodes.
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The presence of pufM was determined by using PCR amplification with specific
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36 primers (Lehours et al., 2010). When necessary, bands of the targeted size were isolated
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from the gel using a DNA gel extraction kit (Millipore, Billerica, MA, USA). Gel-purified
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160 products were concentrated with a Microcon YM50 centrifugal filter devices (Millipore) and
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43 sequenced using pufMF and pufM-WAW primers (Table S2).
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Diversity analysis of pufM gene
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50 A total of 42 DNA samples were extracted as previously described (Marie et al., 2006). To
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165 select samples for pufM diversity analysis, amplification and fingerprinting of pufM
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55 communities using temporal temperature gradient electrophoresis (TTGE) were performed
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57 as described by Lehours et al. (2010). For the construction of partial pufM DNA clone
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Page 9 of 47 FEMS Microbiology Ecology
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3 libraries, fresh PCR products were cloned directly or after gel purification using the TOPO-TA
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5 cloning kit (Invitrogen) according to the manufacturer’s instructions. The sequences were
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170 trimmed to remove any vector and primer sequences. DNA sequences were translated into
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10 amino acid sequences and aligned using the ClustalW program in MEGA 5 (Tamura et al.,
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2011). The resulting protein alignment was back-translated to nucleotide acid sequences
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that were realigned manually. A conservative value of 94% nucleic acid sequence similarity
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17 was chosen for clustering sequences into Operational Taxonomic Units (OTUs) using
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175 MOTHUR (Schloss et al., 2009). Representative sequences (defined as the sequence with the
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22 minimum distance to all rother sequences in the OTU) were obtained using MOTHUR. The
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Shannon
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the bias-corrected richness-estimator, S (Chao et al., 2005) were calculated for each
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31 180 A pufM database containing 35 aligned sequences (720 total nucleotide positions) of
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cultured species and environmental clones retrieved from GenBank and the GOS scaffold
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36 nucleotide sequences was constructed using MEGA 5 (Tamura et al., 2011) according to
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(Yutin et al., 2007). A phylogenetic tree was constructed by Bayesian inference using
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MrBayes with substitution rates varying according to codon positions. Four parallel MCMC
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consensus tree was constructed after the exclusion of 10.000 ‘burnin’ trees. The pufM
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database and the consensus tree were imported into ARB software (Ludwig et al., 2004).
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50 Representative sequences of each OTU (245 pb) and short pufM environmental reference
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sequences were aligned as above and added to the consensus Bayesian tree using the
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55 190 ADD_BY_PARSIMONY algorithm implemented in ARB. Non-informative taxa were removed
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FEMS Microbiology Ecology Page 10 of 47
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3 For cluster analysis, the dataset was randomly resampled before analysis. A distance
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5 matrix was computed from the presence of OTUs in clone libraries at a 94% identity
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threshold using Dice coefficient (Dice, 1945) and a dendrogram was inferred with the
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10 195 unweighted pair-group average algorithm (UPGMA) as implemented in XLSTAT (Addinsoft,
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New York, USA).
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17 In situ abundance of OTU 6 members
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OTU 6, the most abundant group retrieved in the pufM libraries, was targeted by qPCR.
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22 200 Primers targeting specificrally pufM genes from OTU 6 (Table S2) were designed using ARB.
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sequencing 31 clones. All sequences were identical to those of OTU 6 members. QPCR
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29 conditions were as in Table S2. Two plasmid clones from our pufM and 16S rRNA libraries
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31 were used as positive controls and for standard curves (10-fold dilution series) in the qPCR
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205 assays. Plasmid DNA was linearized with HindIII and quantified using the Picogreen assay
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36 (Invitrogen).
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QPCR was performed in triplicate, with 1 µl of environmental sample DNA normalized
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to 100 pg.µl-1 or plasmid DNA solution in a total reaction volume of 10 µl using the SYBR
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43 Green/ROX qPCR Master Mix kit (Applied Biosystems). QPCR assay were performed using a
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210 Chromo4 Real-Time PCR Detection System and the Opticon Monitor software package (Bio-
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Rad) with the following thermal cycling conditions: 95°C for 15 min, 45 cycles of
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50 denaturation at 95°C for 45 s, primer annealing at the primer-specific annealing temperature
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(Table S2) for 45 s with fluorescence measurements after this step, and polymerase
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55 extension at 72°C for 15 s. Melting curves were generated after each assay to check the
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